In the medical field, three-dimensional (3D) image data sets, i.e. volume data sets, are collected by a variety of techniques—referred to as modalities in the field—including ultrasound, computed tomography (CT), and magnetic resonance (MR). Ultrasound images has no absolute grey scale in contrast to, for example, CT where Hounsfield (HU) values define different anatomical structures. This makes classification of tissue difficult in ultrasound imaging. Nevertheless, the use of ultrasound to produce images for medical monitoring and diagnosis has become wide spread to a large extent as a result from its nonionizing nature and its ability to produce images resulting from the inherent differences in mechanical properties of various soft tissues. Typical and common applications include examination and monitoring of the heart, abdomen and fetus. In most areas, diagnosis is now generally based on the size, position, contour and motion of the studied structures as well as on their relative transmission and reflection properties.
When displaying an image, such as in medical imaging applications, particular signal values are associated with particular opacities and also, in case of non-grayscale images, colors to assist visualization. This association or mapping is performed when using data from a 3D data set (voxel data) to compute a 2D data set (pixel data set) which represents a 2D projection of the 3D data set for display on a computer screen or other conventional 2D display apparatus.
Volume data sets contain a larger data quantity than image data sets of 2D images, which is why an evaluation of volume data sets is relatively time-consuming. Therefore, procedures which aid the user in reducing data are necessary and one effective process is known as volume rendering or more generally rendering. In volume rendering, the values in the 3D data set are visualized by a compositing process (projection) along a view direction. The entire depth of the imaged body is thereby acquired. However, details of small objects or structures and especially objects shown in thin layers may be lost and different objects having a similar density may be difficult to separate from each other. The representation is manually characterized by adjustment of “transfer functions”. Illumination effects can be used to improve the visibility of the images.
U.S. Pat. No. 7,457,816 to Barth discloses a method for depicting objects displayed in a first volume data set using volume rendering. A second volume data set is generated in which the volume elements of the first volume data set are modulated and/or coded dependent on a root mean squared depth, parallel to the main observation direction running in the first volume data set. Thereafter, a volume rendering is applied on the second data set.
However, there is still a need within the field of improved methods and systems for volume rendering of medical images and of improved methods and systems for volume rending of medical images obtained using ultrasound imaging systems.